文章基本信息

标题：Analysis of AneuRisk65 data: $k$-mean alignment
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作者：Laura M. Sangalli ; Piercesare Secchi ; Simone Vantini 等
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2014
卷号：8
期号：2
页码：1891-1904
DOI：10.1214/14-EJS938A
语种：English
出版社：Institute of Mathematical Statistics
摘要：We describe the $k$-mean alignment procedure, for the joint alignment and clustering of functional data and we apply it to the analysis of the AneuRisk65 data. Thanks to the efficient separation of the variability in phase variability and within/between clusters amplitude variability, we are able to discriminate subjects having aneurysms in different cerebral districts and identifying different morphological shapes of Inner Carotid Arteries, unveiling a strong association between arteries morphologies and the aneurysmal pathology.